A Linked Data-Based Framework for Personalized Services Information Retrieval in Smart City

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• 作者：Dehai Zhang (20)
  Tianlong Song (21)
  Jin Li (20)
  Qing Liu (20)
  
• 关键词：Linked Data ; Personalized Urban Service Retrieval ; Semantic Cities ; Ontology
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8182
• 期：1
• 页码：461-473
• 全文大小：438 KB
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• 作者单位：Dehai Zhang (20)
  Tianlong Song (21)
  Jin Li (20)
  Qing Liu (20)
  
  20. School of Software, Yunnan University, Kunming City, China
  21. School of Engineering, Univ. of Melbourne, Parkville, VIC, Australia
  
• ISSN：1611-3349

文摘

Recently, personalized services finding in Smart City or Digit City is a hotspot in research area. City and urban areas contain plenty of services but some of them are difficult to extract and retrieval to people. Furthermore, with the development of the Semantic Web, more and more datasets are represented as RDF format and become part of the Linked Data, which provides a fundamentally new venue for personalized urban services retrieval in smart city applications. In this paper, we propose a personalized urban services retrieval framework which is performed by using ontology and comparing RDF-based user profiles with dataset in relation to civic services on web of data. To extract hidden information, the domain specific ontology is involved for linking entities on the web of data. The cases we envisage will show that the proposed framework can effectively return services resources with respect to the user’s interests.